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A. Gangopadhyay and A. R. Robinson

1. Introduction This study focuses on our present-day capability of forecasting the Gulf Stream meander and ring (GSMR) region. Using the Harvard primitive equation (PE) model as the dynamical basis, we investigate three 2-week data-rich periods from a viewpoint of synoptic verification. The initialization fields are based on the kinematic synthesis of multiscale feature models (MSFMs) as described by Gangopadhyay et al. (1997). For comparison, the forecasts are redone with the U.S. Navy

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Lei Han, Shengxue Fu, Lifeng Zhao, Yongguang Zheng, Hongqing Wang, and Yinjing Lin

1. Introduction Storm identification, tracking, and forecasting using radar data are important facets of forecasting the location and strength of severe weather events. Detecting storms, calculating their properties [such as centroid position, vertically integrated liquid water (VIL), volume, top height, etc.], and tracking and forecasting the evolution and movement of the storms make up an essential part of severe weather warning operations. These results can also serve as input to other radar

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Scott M. Glenn and Michael F. Crowley

to evaluate the nowcast and forecast capabilities of dynamical ocean models in the Gulf Stream region (GSR) described above ( Willems et al. 1994 ). To focus the evaluation on model physics under optimal conditions, a 6-week duration test case was formulated during a data-rich time period from the late 1980s. Satellite infrared imagery, Geosat altimetry, and numerous temperature–salinity profiles obtained from several dedicated observation programs were used to construct a series of snapshots of

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Brett T. Hoover and Chris S. Velden

1. Introduction The evaluation of observing system changes on the forecast has been a crucial part of advancing operational numerical weather prediction (NWP), which has seen significant gains in forecast skill in the last few decades through advancement of data assimilation ( Bauer et al. 2015 ). Often, this evaluation is obtained through observing system experiments (OSEs) in which observations are either excluded or added to assimilation, relative to a control, to assess their impact on

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Lohitzune Solabarrieta, Sergey Frolov, Mike Cook, Jeff Paduan, Anna Rubio, Manuel González, Julien Mader, and Guillaume Charria

over 15 cm s −1 have been observed over the slope of the study area during stratified conditions ( Rubio et al. 2011 ). An area characterized by such complex circulation patterns and where relevant human activities linked to marine resources concentrate (artisanal and commercial fishing, tourism, industry, increasing offshore aquaculture and marine renewables, etc.) represents a particular challenge for the accurate monitoring and forecasting of surface transport patterns. In this context, the

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Haibo Zou, Shanshan Wu, Jiusheng Shan, and Xueting Yi

initial conditions (i.e., the model spinup problem; Hwang et al. 2015 ). In addition to NWP, nowcasting can also be accomplished by radar echo extrapolation which is in fact based on the inertia motion of the radar echo pattern. In contrast, such extrapolation-based nowcasting techniques, which are in fact two-dimensional forecasts of rainwater, are more skillful than NWP-based ( Lin et al. 2005 ; Mandapaka et al. 2012 ). Although data (such as radar and satellite) assimilation could improve the

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Sijie Pan, Jidong Gao, David J. Stensrud, Xuguang Wang, and Thomas A. Jones

1. Introduction The goal of the NOAA’s Warn-on-Forecast (WoF) program is to make more accurate forecasts of high-impact weather events, such as tornadoes, hailstorms, flash floods, and damaging windstorms ( Stensrud et al. 2009 ). To accomplish this goal, high-resolution remote sensing data, such as radar and high-resolution satellite data that provide information on internal storm structures, have to be used. Many studies have demonstrated that effective utilization of high-resolution remote

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R. Harikumar, N. K. Hithin, T. M. Balakrishnan Nair, P. Sirisha, B. Krishna Prasad, C. Jeyakumar, Shailesh Nayak, and S. S. C. Shenoi

1. Introduction Safe marine navigation depends crucially on the forecast of ocean state, especially along the ship route. Prior information of the ocean state would highly benefit mariners to ensure the maximum safety and crew comfort, minimum fuel consumption, minimum time underway, or any desired combination of these factors. In recent times, like all other oceans, the Indian Ocean (IO) also experienced an increase in maritime activities, such as transportation, fishing, and sailing, which in

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Hyun-Sook Kim, Carlos Lozano, Vijay Tallapragada, Dan Iredell, Dmitry Sheinin, Hendrik L. Tolman, Vera M. Gerald, and Jamese Sims

1. Introduction Traditionally, short-range weather prediction produced at the U.S. National Weather Service (NWS) is conducted with fixed-in-time distributions of sea surface temperature (SST), assuming its temporal variability has little effect within the forecast range. However, coastal upwelling, boundary currents, eddies, and ocean responses to strong winds significantly affect SST temporal variability and its gradient over a large area. They can also affect atmospheric motions, engaging at

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Edward D. Zaron, Marie-Aude Pradal, Patrick D. Miller, Alan F. Blumberg, Nickitas Georgas, Wei Li, and Julia Muccino Cornuelle

. Hydraul. Eng. , 134 , 403 – 415 . Brent, R. P. , 1973 : An algorithm with guaranteed convergence for finding a zero of a function . Algorithms for Minimization without Derivatives, Prentice Hall, 47–60 . Bruno, M. S. , Blumberg A. F. , and Harrington T. O. , 2006 : The urban ocean observatory—Coastal ocean observations and forecasting in the New York Bight . J. Mar. Sci. Environ. , C4 , 31 – 39 . Chua, B. , and Bennett A. F. , 2001 : An inverse ocean modeling system . Ocean

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